Detecting the oil spill is of paramount importance to have a safe and clean O&G Industry 4.0. The accuracy of DNN-based oil spill detection systems has been promising [1]}. We utilize a detection system that operates based on the FCN-8 model [2]}, which is depicted in Figure REF . As we can see, the model contains five Fully Convolutional Network (FCN) blocks and two up-sampling blocks that collectively perform semantic segmentation (i.e., classifying every pixel) of an input image and output a labeled image. The FCN-8 model functions based on the satellite (a.k.a. SAR) [3]} images. We configure the analysis to obtain the inference time of 110 SAR images collected by MKLab [1]}.
